# readprm.R (filter parameters)
#
#readprm <- function(){

# Notes:
# loc_distype:
# - 'earth' assumes lat lon input coordinates for grid and observation positions
#   then uses great circle distances fr localisation. Still $ll (localisation distance)
#   has to be input in [m]

prm <- list()
prm$method  <- 'ETKF'                        # DA method -- TODO: GLETKF, Green?
prm$rfactor <- 1                             # multiple (scaling) for R (observation error covariance)
prm$loc_boo      <- TRUE                     # whether to conduct localization 0 or 1 [apply to all elements in the augmented state vector]
prm$loc_method   <- 'LA'                     # localization method. 'CF' (covariance filtering), or 'LA' (local analysis)
prm$loc_function <- 'Gaspari_Cohn'           # tag for the localisation function (calc_loccoeffs.m)
prm$loc_distype  <- 'earth'                  # '2D' for Euclidean, or 'SG' for along network distances [apply to all elements in the augmented state vector]
#prm$sgf          <- 'sgriv.rds'             # SpatialGraph representing the river network. Just required if loc_distype=='SG'
#prm$gridSGf      <- 'GgridSG.rds'                                     # precalculated grid-to-SpatialGraph connectivity object [SpatialPointsDataFrame]
prm$rotate       <- FALSE                                             # 0 = do not rotate. 1 = rotate. The code has to prepared to set prm.rotate each some assimilation steps
prm$rotate_ampl  <- 1                                                 # always 1. Code not prepared for other values
#prm$HnnDEM       <- FALSE                                             # whether to use the downstream-transform to obtain HE
#prm$downstrmapf <- 'downstrfilled.asc'                                # downstream map. Just required if HnnDEM == 1 
#return(prm)
#}
